<!DOCTYPE html>
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<title>The Wealth & Health of Nations</title>
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@import url(../style.css?20120427);

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<header>
  <aside>March 13, 2012</aside>
  <a href="../" rel="author">Mike Bostock</a>
</header>

<h1>The Wealth & Health of Nations</h1>

<p id="chart"></p>

<aside>After the animation finishes, mouseover the year to change.</aside>

<p class="attribution">Source: <a href="https://github.com/RandomEtc/mind-gapper-js">Tom Carden</a>.

<p>This is a recreation in <a href="http://d3js.org/">D3</a> of Gapminder’s <a href="http://gapminder.org/world/">Wealth & Health of Nations</a>, made famous by Hans Rosling’s memorable <a href="http://www.ted.com/talks/hans_rosling_shows_the_best_stats_you_ve_ever_seen.html">2006 TED talk</a>. It shows the dynamic fluctuation in per-capita income (<i>x</i>), life expectancy (<i>y</i>) and population (radius) of 180 nations over the last 209 years. Nations are colored by geographic region; mouseover to read their names.

<p>As <a href="http://randometc.github.com/mind-gapper-js/">Tom Carden</a> noted, there’s a surprising amount of work that goes into making something look simple. For one, data collected in recent years is consistent, while data prior to 1950 is sparse; although potentially misleading, these visualizations use <a href="http://en.wikipedia.org/wiki/Lerp_(computing)">linear interpolation</a> for missing data points. The lookup for the two interpolation values at each frame is accelerated using <a href="http://en.wikipedia.org/wiki/Binary_search_algorithm">bisection</a> of sorted arrays per dimension.

<p>Interested to see how this chart was implemented? <a href="https://github.com/mbostock/bost.ocks.org/blob/gh-pages/mike/nations/index.html">View source!</a> Want a fun project? Try adding a <a href="https://github.com/mbostock/d3/wiki/Voronoi-Geom">Voronoi overlay</a> (as in this <a href="http://mbostock.github.com/d3/talk/20111116/airports.html">airport diagram</a>) to improve mouseover interaction on small targets. Or try a static version, using trails instead of motion.


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Pacific","income":[[1800,459.71],[1820,459.71],[1870,440.8],[1913,634.17],[1950,573.94],[1951,589.87],[1952,605.07],[1953,621.19],[1954,638.49],[1955,654.19],[1956,665.99],[1957,676.29],[1958,684.6],[1959,690.41],[1960,696.95],[1961,708.2],[1962,772.05],[1963,769.51],[1964,780.9],[1965,764.66],[1966,749.36],[1967,637.12],[1968,609.88],[1969,644.57],[1970,641.06],[1971,657.68],[1972,699.5],[1973,729.17],[1974,683.26],[1975,619.17],[1976,705.88],[1977,713.54],[1978,702.65],[1979,693.39],[1980,660.36],[1981,668.83],[1982,707.24],[1983,729.51],[1984,777.06],[1985,805.22],[1986,809.93],[1987,820.8],[1988,851.42],[1989,868.8],[1990,893.88],[1991,927.11],[1992,989.02],[1993,1049.36],[1994,1121.67],[1995,1208.14],[1996,1300.38],[1997,1385.9],[1998,1445.95],[1999,1495.63],[2000,1577.53],[2001,1666.51],[2002,1764.46],[2003,1872.13],[2004,1996.87],[2005,2142],[2006,2289.34],[2007,2453.8],[2008,2574.44],[2009,2679.34]],"population":[[1800,6551000],[1820,6551000],[1870,10528000],[1913,19339000],[1950,25348144],[1951,25793577],[1952,26246839],[1953,26724094],[1954,27210027],[1955,27738063],[1956,28327287],[1957,28998543],[1958,29775192],[1959,30682902],[1960,31656282],[1961,32701357],[1962,33796140],[1963,34932464],[1964,36099052],[1965,37258369],[1966,38378468],[1967,39463910],[1968,40511528],[1969,41542068],[1970,42576676],[1971,43614366],[1972,44655014],[1973,45736496],[1974,46902295],[1975,48075207],[1976,49273016],[1977,50533506],[1978,51662728],[1979,52668447],[1980,53715202],[1981,54902677],[1982,56142181],[1983,57436347],[1984,58762040],[1985,60093068],[1986,61439826],[1987,62826491],[1988,64211347],[1989,65868481],[1990,67282704],[1991,68639527],[1992,69940728],[1993,71243961],[1994,72538927],[1995,73772337],[1996,74941175],[1997,76048996],[1998,77092383],[1999,78089676],[2000,79060410],[2001,79999453],[2002,80908147],[2003,81790803],[2004,82662800],[2005,83535576],[2006,84402966],[2007,85262356],[2008,86116559]],"lifeExpectancy":[[1800,32],[1930,32],[1936,33],[1950,39.42],[1951,39.67],[1952,40.17],[1953,40.66],[1954,41.16],[1955,41.65],[1956,42.15],[1957,42.64],[1958,43.13],[1959,43.63],[1960,44.13],[1961,44.62],[1962,45.12],[1963,45.61],[1964,46.11],[1965,46.6],[1966,47.06],[1967,47.49],[1968,47.91],[1969,48.34],[1970,48.82],[1971,49.4],[1972,50.11],[1973,50.95],[1974,51.92],[1975,52.96],[1976,54.01],[1977,55.02],[1978,55.93],[1979,56.74],[1980,57.45],[1981,58.09],[1982,58.71],[1983,59.35],[1984,60.04],[1985,60.8],[1986,61.63],[1987,62.53],[1988,63.47],[1989,64.44],[1990,65.41],[1991,66.35],[1992,67.24],[1993,68.05],[1994,68.79],[1995,69.45],[1996,70.04],[1997,70.59],[1998,71.11],[1999,71.61],[2000,72.08],[2001,72.51],[2002,72.91],[2003,73.26],[2004,73.56],[2005,73.83],[2006,74.07],[2007,74.29],[2008,74.5],[2009,74.7]]},{"name":"Vanuatu","region":"East Asia & Pacific","income":[[1800,829.58],[1820,829.58],[1913,1121.52],[1973,2282.11],[1974,2972.51],[1975,2746.96],[1976,2713.85],[1977,2605.69],[1978,2972.59],[1979,2999.82],[1980,2584.81],[1981,2624.32],[1982,2834.89],[1983,3359.3],[1984,3507.64],[1985,3464.31],[1986,3314.97],[1987,3251.27],[1988,3191.44],[1989,3217.72],[1990,3281.56],[1991,3574.86],[1992,3443.42],[1993,3492.04],[1994,3482.08],[1995,3555.62],[1996,3729.75],[1997,3840.47],[1998,3936.02],[1999,3741.1],[2000,3762.19],[2001,3575.45],[2002,3234.46],[2003,3251.04],[2004,3340.51],[2005,3477],[2006,3632.57],[2007,3779.08],[2008,3916.57],[2009,3943.3]],"population":[[1800,27791],[1820,27791],[1950,52000],[1951,53262],[1952,54554],[1953,55878],[1954,57233],[1955,58622],[1956,60044],[1957,61501],[1958,62993],[1959,64522],[1960,66087],[1961,67691],[1962,69333],[1963,71015],[1964,72577],[1965,74195],[1966,76132],[1967,78219],[1968,80571],[1969,82905],[1970,85400],[1971,88100],[1972,90800],[1973,93700],[1974,96600],[1975,99700],[1976,102800],[1977,106000],[1978,109400],[1979,113399],[1980,116771],[1981,120223],[1982,123745],[1983,127335],[1984,130982],[1985,134677],[1986,138418],[1987,142207],[1988,146040],[1989,149913],[1990,153785],[1991,157616],[1992,161399],[1993,165127],[1994,168793],[1995,172387],[1996,175927],[1997,179428],[1998,182882],[1999,186282],[2000,189618],[2001,192910],[2002,196178],[2003,199414],[2004,202609],[2005,205754],[2006,208869],[2007,211971],[2008,215053]],"lifeExpectancy":[[1950,40.8],[1951,41.1],[1952,41.7],[1953,42.3],[1954,42.9],[1955,43.5],[1956,44.1],[1957,44.7],[1958,45.3],[1959,45.9],[1960,46.5],[1961,47.1],[1962,47.7],[1963,48.3],[1964,48.9],[1965,49.5],[1966,50.1],[1967,50.7],[1968,51.3],[1969,51.9],[1970,52.5],[1971,53.1],[1972,53.7],[1973,54.3],[1974,54.9],[1975,55.5],[1976,56.12],[1977,56.74],[1978,57.36],[1979,57.98],[1980,58.58],[1981,59.14],[1982,59.65],[1983,60.11],[1984,60.52],[1985,60.92],[1986,61.34],[1987,61.8],[1988,62.32],[1989,62.9],[1990,63.51],[1991,64.11],[1992,64.66],[1993,65.14],[1994,65.53],[1995,65.87],[1996,66.15],[1997,66.44],[1998,66.73],[1999,67.06],[2000,67.42],[2001,67.8],[2002,68.18],[2003,68.56],[2004,68.92],[2005,69.26],[2006,69.58],[2007,69.89],[2008,70.2],[2009,70.5]]}]

readJson = function(text, callback)
{
  callback(text ? JSON.parse(text) : null);
}

// Various accessors that specify the four dimensions of data to visualize.
function x(d) { return d.income; }
function y(d) { return d.lifeExpectancy; }
function radius(d) { return d.population; }
function color(d) { return d.region; }
function key(d) { return d.name; }

// Chart dimensions.
var margin = {top: 19.5, right: 19.5, bottom: 19.5, left: 39.5},
    width = 960 - margin.right,
    height = 500 - margin.top - margin.bottom;

// Various scales. These domains make assumptions of data, naturally.
var xScale = d3.scale.log().domain([300, 1e5]).range([0, width]),
    yScale = d3.scale.linear().domain([10, 85]).range([height, 0]),
    radiusScale = d3.scale.sqrt().domain([0, 5e8]).range([0, 40]),
    colorScale = d3.scale.category10();

// The x & y axes.
var xAxis = d3.svg.axis().orient("bottom").scale(xScale).ticks(12, d3.format(",d")),
    yAxis = d3.svg.axis().scale(yScale).orient("left");

// Create the SVG container and set the origin.
var svg = d3.select("#chart").append("svg")
    .attr("width", width + margin.left + margin.right)
    .attr("height", height + margin.top + margin.bottom)
  .append("g")
    .attr("transform", "translate(" + margin.left + "," + margin.top + ")");

// Add the x-axis.
svg.append("g")
    .attr("class", "x axis")
    .attr("transform", "translate(0," + height + ")")
    .call(xAxis);

// Add the y-axis.
svg.append("g")
    .attr("class", "y axis")
    .call(yAxis);

// Add an x-axis label.
svg.append("text")
    .attr("class", "x label")
    .attr("text-anchor", "end")
    .attr("x", width)
    .attr("y", height - 6)
    .text("income per capita, inflation-adjusted (dollars)");

// Add a y-axis label.
svg.append("text")
    .attr("class", "y label")
    .attr("text-anchor", "end")
    .attr("y", 6)
    .attr("dy", ".75em")
    .attr("transform", "rotate(-90)")
    .text("life expectancy (years)");

// Add the year label; the value is set on transition.
var label = svg.append("text")
    .attr("class", "year label")
    .attr("text-anchor", "end")
    .attr("y", height - 24)
    .attr("x", width);

// Load the data.
readJson(JSON.stringify(jsonData), function(nations) {

  // A bisector since many nation's data is sparsely-defined.
  var bisect = d3.bisector(function(d) { return d[0]; });

  // Add a dot per nation. Initialize the data at 1800, and set the colors.
  var dot = svg.append("g")
      .attr("class", "dots")
    .selectAll(".dot")
      .data(interpolateData(1800))
    .enter().append("circle")
      .attr("class", "dot")
      .style("fill", function(d) { return colorScale(color(d)); })
      .call(position)
      .sort(order);

  // Add a title.
  dot.append("title")
      .text(function(d) { return d.name; });

  // Start a transition that interpolates the data based on year.
  svg.transition()
      .duration(30000)
      .ease("linear")
      .tween("year", tweenYear)
      .each("end", enableInteraction);

  // Positions the dots based on data.
  function position(dot) {
    dot .attr("cx", function(d) { return xScale(x(d)); })
        .attr("cy", function(d) { return yScale(y(d)); })
        .attr("r", function(d) { return radiusScale(radius(d)); });
  }

  // Defines a sort order so that the smallest dots are drawn on top.
  function order(a, b) {
    return radius(b) - radius(a);
  }

  // After the transition finishes, you can mouseover to change the year.
  function enableInteraction() {
    var box = label.node().getBBox();

    var yearScale = d3.scale.linear()
        .domain([1800, 2009])
        .range([box.x + 10, box.x + box.width - 10])
        .clamp(true);

    svg.append("rect")
        .attr("class", "overlay")
        .attr("x", box.x)
        .attr("y", box.y)
        .attr("width", box.width)
        .attr("height", box.height)
        .on("mouseover", mouseover)
        .on("mouseout", mouseout)
        .on("mousemove", mousemove)
        .on("touchmove", mousemove);

    function mouseover() {
      label.classed("active", true);
    }

    function mouseout() {
      label.classed("active", false);
    }

    function mousemove() {
      displayYear(yearScale.invert(d3.mouse(this)[0]));
    }
  }

  // Tweens the entire chart by first tweening the year, and then the data.
  // For the interpolated data, the dots and label are redrawn.
  function tweenYear() {
    var year = d3.interpolateNumber(1800, 2009);
    return function(t) { displayYear(year(t)); };
  }

  // Updates the display to show the specified year.
  function displayYear(year) {
    dot.data(interpolateData(year), key).call(position).sort(order);
    label.text(Math.round(year));
  }

  // Interpolates the dataset for the given (fractional) year.
  function interpolateData(year) {
    return nations.map(function(d) {
      return {
        name: d.name,
        region: d.region,
        income: interpolateValues(d.income, year),
        population: interpolateValues(d.population, year),
        lifeExpectancy: interpolateValues(d.lifeExpectancy, year)
      };
    });
  }

  // Finds (and possibly interpolates) the value for the specified year.
  function interpolateValues(values, year) {
    var i = bisect.left(values, year, 0, values.length - 1),
        a = values[i];
    if (i > 0) {
      var b = values[i - 1],
          t = (year - a[0]) / (b[0] - a[0]);
      return a[1] * (1 - t) + b[1] * t;
    }
    return a[1];
  }
});

</script>
